Precise Tradeoffs in Adversarial Training for Linear Regression

24 February 2020

Papers citing "Precise Tradeoffs in Adversarial Training for Linear Regression"

50 / 83 papers shown

Title
Towards Better Generalization via Distributional Input Projection Network Yifan Hao Yanxin Lu Xinwei Shen Tong Zhang 95 0 0 05 Jun 2025
LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders Borna Khodabandeh Amirabbas Afzali Amirhossein Afsharrad Seyed Shahabeddin Mousavi Sanjay Lall Sajjad Amini Seyed-Mohsen Moosavi-Dezfooli AAML 33 0 0 24 May 2025
Risk Analysis and Design Against Adversarial Actions M. Campi A. Carè Luis G. Crespo S. Garatti Federico A. Ramponi AAML 445 0 0 02 May 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs Kasimir Tanner Matteo Vilucchio Bruno Loureiro Florent Krzakala AAML 97 1 0 31 Dec 2024
Learning Fair Robustness via Domain Mixup Meiyu Zhong Ravi Tandon OOD 119 0 0 21 Nov 2024
Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization Diana Pfau Alexander Jung 75 1 0 25 Oct 2024
Robust Feature Learning for Multi-Index Models in High Dimensions Alireza Mousavi-Hosseini Adel Javanmard Murat A. Erdogdu OOD AAML 170 1 0 21 Oct 2024
Efficient Optimization Algorithms for Linear Adversarial Training Antônio H. Ribeiro Thomas B. Schon Dave Zahariah Francis Bach AAML 112 2 0 16 Oct 2024
Investigating the Impact of Model Complexity in Large Language Models Jing Luo Huiyuan Wang Weiran Huang 62 0 0 01 Oct 2024
Criticality Leveraged Adversarial Training (CLAT) for Boosted Performance via Parameter Efficiency Bhavna Gopal Huanrui Yang Jingyang Zhang Mark Horton Yiran Chen AAML 83 0 0 19 Aug 2024
Towards unlocking the mystery of adversarial fragility of neural networks Jingchao Gao Raghu Mudumbai Xiaodong Wu Jirong Yi Catherine Xu Hui Xie Weiyu Xu 60 1 0 23 Jun 2024
High-dimensional (Group) Adversarial Training in Linear Regression Yiling Xie Xiaoming Huo 100 2 0 22 May 2024
$H$ -Consistency Guarantees for Regression Anqi Mao M. Mohri Yutao Zhong 83 9 0 28 Mar 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective Yue Xing Xiaofeng Lin Qifan Song Yi Tian Xu Belinda Zeng Guang Cheng SSL 54 0 0 26 Jan 2024
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions Adel Javanmard Lin Chen Vahab Mirrokni Ashwinkumar Badanidiyuru Gang Fu 57 2 0 20 Jan 2024
The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness Yifan Hao Tong Zhang AAML 144 5 0 19 Jan 2024
Regularization properties of adversarially-trained linear regression Antônio H. Ribeiro Dave Zachariah Francis Bach Thomas B. Schön AAML 79 11 0 16 Oct 2023
Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization Adel Javanmard Vahab Mirrokni 76 2 0 06 Oct 2023
SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks Alexander Robey Eric Wong Hamed Hassani George J. Pappas AAML 170 259 0 05 Oct 2023
Ensemble linear interpolators: The role of ensembling Mingqi Wu Qiang Sun 77 2 0 06 Sep 2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models Changyu Liu Yuling Jiao Junhui Wang Jian Huang AAML 41 2 0 02 Sep 2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms Elvis Dohmatob M. Scetbon AAML OOD 68 1 0 01 Aug 2023
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning Kaijie Zhu Jindong Wang Xixu Hu Xingxu Xie G. Yang AAML 74 25 0 01 Aug 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering Anselm Krainovic Mahdi Soltanolkotabi Reinhard Heckel OOD 48 7 0 24 Jul 2023
Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training Masaaki Imaizumi AAML 68 4 0 08 Jul 2023
Adversarial Training with Generated Data in High-Dimensional Regression: An Asymptotic Study Yue Xing 44 0 0 21 Jun 2023
Adversarial Training Should Be Cast as a Non-Zero-Sum Game Alexander Robey Fabian Latorre George J. Pappas Hamed Hassani Volkan Cevher AAML 158 13 0 19 Jun 2023
On Achieving Optimal Adversarial Test Error Justin D. Li Matus Telgarsky AAML 62 2 0 13 Jun 2023
On the ISS Property of the Gradient Flow for Single Hidden-Layer Neural Networks with Linear Activations A. C. B. D. Oliveira Milad Siami Eduardo Sontag 105 2 0 17 May 2023
Enhancing Robustness of Gradient-Boosted Decision Trees through One-Hot Encoding and Regularization Shijie Cui Agus Sudjianto Aijun Zhang Runze Li AI4CE 98 11 0 26 Apr 2023
Understanding Overfitting in Adversarial Training via Kernel Regression Teng Zhang Kang Li 56 2 0 13 Apr 2023
Reliable learning in challenging environments Maria-Florina Balcan Steve Hanneke Rattana Pukdee Dravyansh Sharma OOD 80 6 0 06 Apr 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 111 37 0 19 Mar 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 98 11 0 17 Mar 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels Simone Bombari Shayan Kiyani Marco Mondelli AAML 134 10 0 03 Feb 2023
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond M. Scetbon Elvis Dohmatob AAML 48 3 0 31 Jan 2023
Adversarial training with informed data selection Marcele O. K. Mendonça Javier Maroto P. Frossard P. Diniz AAML 47 4 0 07 Jan 2023
A Theoretical Study of The Effects of Adversarial Attacks on Sparse Regression Deepak Maurya Jean Honorio AAML 64 0 0 21 Dec 2022
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria Tengyuan Liang 74 1 0 05 Dec 2022
Adversarial Rademacher Complexity of Deep Neural Networks Jiancong Xiao Yanbo Fan Ruoyu Sun Zhimin Luo AAML 60 23 0 27 Nov 2022
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games Maria-Florina Balcan Rattana Pukdee Pradeep Ravikumar Hongyang R. Zhang AAML 97 12 0 23 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training Jiancong Xiao Yanbo Fan Ruoyu Sun Jue Wang Zhimin Luo AAML 83 31 0 03 Oct 2022
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness Mazda Moayeri Kiarash Banihashem Soheil Feizi OOD 124 23 0 15 Sep 2022
Surprises in adversarially-trained linear regression Antônio H. Ribeiro Dave Zachariah Thomas B. Schon AAML 182 2 0 25 May 2022
Overparameterized Linear Regression under Adversarial Attacks Antônio H. Ribeiro Thomas B. Schon AAML 53 19 0 13 Apr 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 40 19 0 03 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 92 13 0 26 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min Lin Xiao Yang Junyi Zhu Shuicheng Yan 120 124 0 21 Feb 2022
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness Yue Xing Qifan Song Guang Cheng 51 4 0 14 Feb 2022
Probabilistically Robust Learning: Balancing Average- and Worst-case Performance Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani AAML OOD 109 43 0 02 Feb 2022